While I believe that will be the case in the near future (if it isn’t already the case today), the data center of tomorrow has the potential to add complexity to the organization’s IT systems and platforms. This complexity may just be a simple replacement of other types of complexity or it may be adding complexity to the data center. Either way, complexity has the potential to be an agility killer if it isn’t managed or planned for correctly.

Complexity has always existed within the data center. From the first day of data center existence, IT professionals have had to manage complexity but in recent years there’s been quite a bit of growth in complex systems within the data center. With companies increasing their use of virtualization within their data centers, connecting data centers with the cloud and implementing new platforms and systems every year, the level of complexity continues to increase.

Without proper thinking and planning, this complexity can have a negative effect on agility within the data center. There are a few things that organizations can do to attempt to manage complexity within the data center while keeping agility at the forefront of the IT group and the data center. A few ideas for managing complexity are:

Get visibility into the platforms throughout the organization to ensure that the IT group understands what platforms the business has

Get visibility beyond the platforms to allow IT to understand the business processes that are driving platform changes

Ensure open communication channels between all groups within the business to ensure when a new platform is needed or wanted, IT is informed and involved in the decision making process

Have a proper business technology strategy that drives all technology projects.

Build a technology council and invite members from all areas of the business to allow different opinions and insights into the technology strategy of the organization

As you can see from these ideas may not seem that great at first, they are a starting point for understanding the technological systems and platforms within the company. By understanding your platforms, you can understand the complexity that exists (or might exist in the future) and help keep agility alive.

About Eric

Eric received his Doctor of Science (D.Sc.) in Information Systems in 2014 with a dissertation titled "Analysis of Twitter Messages for Sentiment and Insight for use in Stock Market Decision Making". His research interests are currently in the areas of decision support, data science, big data, natural language processing, sentiment analysis and social media analysis.In recent years, he has combined sentiment analysis, natural language processing and big data approaches to build innovative systems and strategies to solve interesting problems.

In addition, he is an entrepreneur that has launched a few companies with the most recent being a company focused on proving data analytics and visualization services to the financial markets.